Adolescent idiopathic scoliosis (AIS) is a multi-factorial, three-dimensional deformity of the spine and trunk which can appear and sometimes progress during any of the rapid periods of growth in apparently healthy children. Generally, AIS patients are first diagnosed between the ages of 10 to 15 years old with skeletal maturity. Patients with early scoliosis or a Cobb's angle of 10-20 degrees only need to attend regular check-ups every 6 to 12 months. However, those patients with a spinal curvature of 21-45 degrees may undergo various kinds of therapy, whereas when the spinal curvature is over 45°, surgery is recommended by filling the vertebrae with bone through fusion to the spinal disc and thus straightening the spine [2]. For non-surgical and non-medical interventions for patients with a spinal curvature of 21-45 degrees, conventional orthotic interventions apply passive forces to the human body with orthosis with the use of a brace made of rigid plastic material to support the trunk alignment and control the deformities of the spine [4]. However, the use of these external supports is limited by factors such as poor appearance, bulkiness, physical constraint, skin irritation, and muscle atrophy that could lead to low acceptance and compliance. There are no differences even if a flexible brace, which is made of elastic bands, is used instead of a rigid brace [3]. Back muscle strengthening exercises attempt to strengthen the back muscles to maintain the trunk in an upright position with active muscular forces. However, patient compliance with the prescribed intervention exercises present a challenge, especially patients who are not self-motivated may not continue with the prescribed exercise programs.
There are a few existing works focusing on adopting sensor-based technology in treating idiopathic scoliosis. In WO2013110835A1, a programmable subcutaneous or submuscular device is proposed to collect/record electromyographic signals and stimulate that part of the deep paraspinal muscles that is affected by the pathology. The muscle stimulation is controlled by control logic that comprises a feedback-loop algorithm for adjustment of the stimulation on the basis of the results obtained from the sensors. There are many drawbacks regarding to this design. First, it is intrusive. The submuscular module requires proper procedure to be implanted into human body. This requirement largely affects comfort and compliance of the system, and even causes side effects such as infection. Second, it relies on a naive feedback loop. The feedback loop is implemented locally using predefined control logic. This imposes difficulty in modifying the feedback algorithm once the device is setup. More importantly, it has intrinsic inability to support adaptation of the feedback logic based either on the historical information such as patient's progress, or on external information such as doctor/specialists' opinion. Third, wired connection is adopted on the body area. Compared to wireless setup, wired design is less flexible, and less comfortable for the patient. Fourth, only electromyography is considered. It lacks the consideration of other important factors like patient's motion, posture, etc.
In U.S. Pat. No. 5,082,002A, a system and method for the operant conditioning of subjects using biofeedback is proposed. The design provides means to measure a variable condition, such as posture, which is controllable by the subject. The apparatus sets criteria, which, if not met, may result in a negative reinforcement, such as unpleasant audio tone or, if the criteria are met, will reward the subject. The criterion is automatically adjusted, upwards or downwards, in accordance with the subject's history of reaching, or not reaching, the criteria. Even though this design considered the aspect of adaptation, the adaptation method it used is very primitive—it is achieved by adjusting criteria upwards or downwards. In applications, however, the criteria are hard to set because multiple metrics (resulting to multitude of criteria) should be considered, let alone each criterion should vary from patient to patient. Hence, simply using criterion-based detection in this scenario is not sufficient. Another drawback of this design is that it proposed a tension-based sensor to detect the posture of the patients. Compared to a modern motion sensor, which utilizes accelerometer and gyroscope, the tension-based sensor lacks precision, flexibility, and is prone to error (due to the strict placement requirement).
In U.S. Pat. No. 6,984,208B2, a method for indirectly assessing the gesture, posture or movement of a body part of a person includes transmitting an ultrasound signal into the soft tissue of body part and manipulating the reflected ultrasound signal to obtain parameter data is provided. The method comprises applying an ultrasound transmitter and receiver to a musculoskeletal body part; transmitting an ultrasound signal into soft tissue of the body part and receiving a reflected and/or scattered ultrasound signal at the receiver; manipulating the ultrasound signal to obtain parameter data, including the amplitude, phase, flight-time, frequency spectrum and waveform pattern of the signal, and comparing the parameter data to reference information to obtain a gesture, posture, or movement of the body part. However, the effectiveness of the system for posture correction depends on its ability to remind the patient about his/her spinal curvature, either by alerting the patient of poor posture or by motivating him/her to straighten his/her spine. On this aspect, this proposed system is not preferable for a lack of effective means to stimulate and facilitate the patient in achieving an improvement in the posture in a progressive manner as a treatment for AIS.
Regarding the posture control, which is a major consideration for AIS treatment, the state-of-the art posture correction techniques usually consist of three abstract components: (1) feedback loop; (2) posture sensors; and (3) feedback means. Existing works on posture control are summarized in accordance with each respective component as follows.
Most of the designs, e.g., in WO2013110835A1, US20130108995A1, U.S. Pat. No. 8,157,752B2, U.S. Pat. No. 7,850,574B2, US20090054814A1, WO2006062423A1, U.S. Pat. No. 6,673,027B2 and U.S. Pat. No. 6,579,248B1, adopted a feedback loop with predefined (normally hardcoded) control logic, which we name as a naive feedback loop. The control logic or switch circuit is normally established based on one or a few preset criteria. The feedback means (such as an audio alert) is triggered when given criterion are reached. The whole control flow is normally implemented in hardware (using a switch circuit) as in U.S. Pat. Nos. 5,158,089A, 5,082,002A, 4,914,423A, 4,750,480A, 4,730,625A, 4,007,733A and 5,168,264A, or is hardcoded in software control logic on microcontrollers as in US20130108995A1, WO2013110835A1 and U.S. Pat. No. 8,157,752B2. As mentioned before, the naive feedback mechanism imposes difficulty in modifying the feedback algorithm once the device is set-up. More importantly, it has intrinsic inability to support adaptable feedback logic. Even with a training process implemented for updating the reference signals, as in U.S. Pat. No. 6,984,208B2, the reference information is still based on some typical postures when training the apparatus, which is similar to the abovementioned naive feedback mechanism with difficulties in correcting the data or adapting to changes after completing the training.
As for posture sensors, inclination (also pendulum) (U.S. Pat. Nos. 5,168,264A, 5,158,089A, US20090054814A1), tension (U.S. Pat. Nos. 4,007,733A, 4,914,423A, 5,082,002A, 5,728,027A, 6,384,729B1, 6,579,248B1, WO2006062423A1, US20080319364A1 and U.S. Pat. No. 8,083,693B1), flowable substance (U.S. Pat. No. 7,980,141B2), hinge (U.S. Pat. No. 6,673,027B2), distance between body and sensor (U.S. Pat. No. 8,157,752B2), have been used as sensory means for posture detection in earlier designs. While effectiveness of these methods is largely dependent on the application area and the positioning of sensory devices, the accuracy of a reading cannot always be maintained on an acceptable confidence level. Therefore, to be able to adopt these methods, a more sophisticated design is applied, leading to a poor appearance, bulkiness, and one or more physical constraints in a final design, all of which would in turn affect effectiveness and compliance of the devices. There are some designs embracing modern motion detection approaches that use accelerometers (or combined with gyroscopes), as in U.S. Pat. No. 6,984,208B2, US20110063114A and US20130108995A1. Using such type of sensors can acquire more reliable data inputs and enable more flexible designs. However, providing an efficient detection mechanism that fully utilizes such sensor readings is still a challenging issue. Especially in the area of posture correction, it is impossible to define an absolutely correct posture out of the measurement provided by the sensors. In this case, the naive feedback algorithm with a threshold-based detection algorithm that most existing works have proposed would not suffice.
Very limited feedback means have been adopted in existing techniques. Specifically, only sound and vibration are utilized in a form of alert (a.k.a. notification). However, as mobile devices such as smartphones and tablets have become increasingly pervasive, more user-friendly feedback means can be advantageously provided through those devices. To be more specific, feedback should not only limited to the form of alert, but integrated into existing mobile devices, providing progressive and tailored posture training to patient with AIS with a view to restore a balance in muscle activities and to reduce the displacement of both sides of the spine.
There is a need in the art to have improved methods and apparatus over existing ones as a treatment for AIS.